Chapter 3: The purity analysis

2022 ◽  
Vol 2022 (1) ◽  
pp. i-3-26
Keyword(s):  
Purity Analysis

Evaluation of the Efficiency of Protein A Affinity Chromatography to Purify a Monoclonal Antibody for Cancer Treatment and its Purity Analysis

2020 ◽  
Vol 7 (2) ◽  
pp. 121-133
Author(s):  
Ayesha Akhtar ◽  
Shivakumar Arumugam ◽  
Shoaib Alam
Keyword(s):  
Monoclonal Antibody ◽  
Monoclonal Antibodies ◽  
Affinity Chromatography ◽  
Protein A ◽  
Exchange Chromatography ◽  
Size Exclusion ◽  
High Yield ◽  
Staphylococcal Protein A ◽  
Purification Step ◽  
Purity Analysis

Background:: Protein A affinity chromatography is often employed as the most crucial purification step for monoclonal antibodies to achieve high yield with purity and throughput requirements. Introduction:: Protein A, also known as Staphylococcal protein A (SPA) is found in the cell wall of the bacteria staphylococcus aureus. It is one of the first discovered immunoglobulin binding molecules and has been extensively studied since the past few decades. The efficiency of Protein A affinity chromatography to purify a recombinant monoclonal antibody in a cell culture sample has been evaluated, which removes 99.0% of feed stream impurities. Materials and Method:: We have systematically evaluated the purification performance by using a battery of analytical methods SDS-PAGE (non-reduced and reduced sample), Cation Exchange Chromatography (CEX), Size-exclusion chromatography (SEC), and Reversed phased-Reduced Chromatography for a CHO-derived monoclonal antibody. Results and Discussion:: The analytical test was conducted to determine the impurity parameter, Host Cell Contaminating Proteins (HCP). It was evaluated to be 0.015ng/ml after the purification step; while initially, it was found to be 24.431ng/ml. Conclusion:: The tests showed a distinct decrease in the level of different impurities after the chromatography step. It can be concluded that Protein A chromatography is an efficient step in the purification of monoclonal antibodies.

scholarly journals A tool for finding inclusion clusters in steel SEM specimens

2020 ◽  
Vol 10 (1) ◽  
pp. 642-648
Author(s):  
Anna-Mari Wartiainen ◽  
Markus Harju ◽  
Satu Tamminen ◽  
Leena Määttä ◽  
Tuomas Alatarvas ◽  
...  
Keyword(s):  
Prediction Models ◽  
Microscopic Analysis ◽  
Steel Specimen ◽  
Sem Analysis ◽  
Quality Prediction ◽  
Automatic Production ◽  
Automatic Interpretation ◽  
Metallic Inclusions ◽  
Purity Analysis ◽  
Inclusions In Steel

AbstractNon-metallic inclusions, especially large or clustered inclusions, in steel are usually harmful. Thus, the microscopic analysis of test specimens is an important part of the quality control. This steel purity analysis produces a large amount of individual inclusion information for each test specimen. The interpretation of the results is laborious and the comparison of larger product groups practically impossible. The purpose of this study was to develop an easy-to-use tool for automatic interpretation of the SEM analysis to differentiate clustered and large inclusions information from the manifold individual inclusion information. Because of the large variety of the potential users, the tool needs to be applicable for any steel grade and application, both for liquid and final product specimen, to analyse automatically steel specimen inclusions, especially inclusion clusters, based on the INCA Feature program produced data from SEM/EDS. The developed tool can be used to improve the controlling of the steel purity or for automatic production of new inclusion cluster features that can be utilised further in quality prediction models, for example.

scholarly journals Center-of-mass interpretation for bipartite purity analysis ofN-party entanglement

2016 ◽  
Vol 94 (3) ◽  
Author(s):  
Miguel A. Alonso ◽  
Xiao-Feng Qian ◽  
J. H. Eberly
Keyword(s):  
Center Of Mass ◽  
Purity Analysis

Genetic purity analysis of cotton (Gossypium spp.) hybrids using SSR markers

2010 ◽  
Vol 38 (2) ◽  
pp. 358-366 ◽  
Author(s):  
P. Selvakumar ◽  
R. Ravikesavan ◽  
A. Gopikrishnan ◽  
K. Thiyagu ◽  
S. Preetha ◽  
...  
Keyword(s):  
Ssr Markers ◽  
Genetic Purity ◽  
Gossypium Spp ◽  
Purity Analysis

scholarly journals Determination of the melting temperature, heat of fusion, and purity analysis of different samples of zidovudine (AZT) using DSC

2010 ◽  
Vol 46 (1) ◽  
pp. 37-43 ◽  
Author(s):  
Adriano Antunes Souza Araújo ◽  
Marília dos Santos Bezerra ◽  
Sílvia Storpirtis ◽  
Jivaldo do Rosário Matos
Keyword(s):  
The United States ◽  
Raw Material ◽  
Heat Of Fusion ◽  
Average Value ◽  
Purity Analysis ◽  
Temperature Heat ◽  
Chemical Purity ◽  
Dsc Curves ◽  
States Pharmacopeia

The determination of chemical purity, melting range, and variation of enthalpy in the process of characterizing medicines is one of the principal requirements evaluated in quality control of the pharmaceutical industry. In this study, the method of purity determination using DSC was outlined, as well as the application of this technique for the evaluation of commercial samples of zidovudine (AZT) (raw material) supplied by different laboratories. To this end, samples from six different laboratories (A, B, C, D, E, and F) and the standard reference (R) from the United States Pharmacopeia (USP) were analyzed. The DSC curves were obtained in the temperature range of 25 to 200 ºC under the dynamic atmosphere of N2 (50 mL min-1), heating rate of β=2 ºC min-1, using an Al capsule containing approximately 2 mg of sample material. The results demonstrated that the standard reference presented a proportion of 99.83% whereas the AZT samples presented a variation ranging from 97.59 to 99.54%. In addition, the standard reference was found to present a temperature of onset of melting point of 122.80 °C. Regarding the samples of active agents provided by the different laboratories, a variation ranging from 118.70 to 122.87 °C was measured. In terms of ΔHm, the samples presented an average value of 31.12 kJ mol-1.

scholarly journals Molecular characterization and genetic diversity studies of Indian soybean (Glycine max (L.) Merr.) cultivars using SSR markers

2021 ◽  
Author(s):  
S. P. Jeevan Kumar ◽  
C. Susmita ◽  
K. V. Sripathy ◽  
Dinesh K. Agarwal ◽  
Govind Pal ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Molecular Characterization ◽  
Ssr Markers ◽  
Crop Yield ◽  
Gene Pool ◽  
Stress Factors ◽  
Soybean Cultivars ◽  
Genetic Base ◽  
Purity Analysis ◽  
Breeding Programmes

Abstract Background The genetic base of soybean cultivars in India has been reported to be extremely narrow, due to repeated use of few selected and elite genotypes as parents in the breeding programmes. This ultimately led to the reduction of genetic variability among existing soybean cultivars and stagnation in crop yield. Thus in order to enhance production and productivity of soybean, broadening of genetic base and exploring untapped valuable genetic diversity has become quite indispensable. This could be successfully accomplished through molecular characterization of soybean genotypes using various DNA based markers. Hence, an attempt was made to study the molecular divergence and relatedness among 29 genotypes of soybean using SSR markers. Methods and results A total of 35 SSR primers were deployed to study the genetic divergence among 29 genotypes of soybean. Among them, 14 primer pairs were found to be polymorphic producing a total of 34 polymorphic alleles; and the allele number for each locus ranged from two to four with an average of 2.43 alleles per primer pair. Polymorphic information content (PIC) values of SSRs ranged from 0.064 to 0.689 with an average of 0.331. The dendrogram constructed based on dissimilarity indices clustered the 29 genotypes into two major groups and four sub-groups. Similarly, principal coordinate analysis grouped the genotypes into four major groups that exactly corresponded to the clustering of genotypes among four sub-groups of dendrogram. Besides, the study has reported eight unique and two rare alleles that could be potentially utilized for genetic purity analysis and cultivar identification in soybean. Conclusion In the present investigation, two major clusters were reported and grouping of large number of genotypes in each cluster indicated high degree of genetic resemblance and narrow genetic base among the genotypes used in the study. With respect to the primers used in the study, the values of PIC and other related parameters revealed that the selected SSR markers are moderately informative and could be potentially utilized for diversity analysis of soybean. The clustering pattern of dendrogram constructed based on SSR loci profile displayed good agreement with the cultivar’s pedigree information. High level of genetic similarity observed among the genotypes from the present study necessitates the inclusion of wild relatives, land races and traditional cultivars in future soybean breeding programmes to widen the crop gene pool. Thus, hybridization among diverse gene pool could result in more heterotic combinations ultimately enhancing genetic gain, crop yield and resistance to various stress factors.

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